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INDONESIA
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Published by Universitas Brawijaya
ISSN : -     EISSN : -     DOI : -
Core Subject : Science, Education, Engineering,
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering
Jurnal Pengembangan Teknlogi Informasi dan Ilmu Komputer (J-PTIIK) Universitas Brawijaya merupakan jurnal keilmuan dibidang komputer yang memuat tulisan ilmiah hasil dari penelitian mahasiswa-mahasiswa Fakultas Ilmu Komputer Universitas Brawijaya. Jurnal ini diharapkan dapat mengembangkan penelitian dan memberikan kontribusi yang berarti untuk meningkatkan sumber daya penelitian dalam Teknologi Informasi dan Ilmu Komputer.
Arjuna Subject : -
Articles 6,972 Documents
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Evaluasi Pengalaman Pengguna Pada Aplikasi Perangkat Bergerak Mandiri Online Dengan Metode UX Curve Faris Lafito Hendratna; Hanifah Muslimah Az-Zahra; Yusi Tyroni Mursityo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 13 (2021): Publikasi Khusus Tahun 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Untuk dipublikasikan ke Jurnal RESTI Ikatan Ahli Informatika Indonesia (SINTA 2)
Sistem Pendeteksi dan Pengenalan Rambu Pembatas Kecepatan menggunakan Jaringan Syaraf Tiruan berbasis Raspberry Pi Alvin Evaldo Darmawan; Fitri Utaminingrum
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 9 (2020): September 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Speed ​​limit traffic signs are signs that used to limit vehicle speed. But many drivers break the sign rule because intentionally or unintentionally, resulting in accidents that endanger yourself or others. So, we need a tool that can detect and give a warning to drivers. The system developed in this study detects speed limit traffic signs and perform recognition. The system will detect the color and shape of traffic signs to detect these signs by using color segmentation and Hough Circle Transform. The average accuracy of the system in detecting signs is 94.45%. Next is character detection to separate each character. Character detection is done by color segmentation and Bounding Box for each character. The average accuracy in detecting characters is 88.89%. Furthermore, the character image will be extracted using the division area and the ratio of the foreground pixel to pixel area in each area. The feature extraction results obtained 25 features as input from the Artificial Neural Network to do recognition using the Back-Propagation training algorithm. The average accuracy of the system in doing character recognition is 88.89%. While the average total system computing time is 0.227 seconds.
Pengembangan Sistem Monitoring Smarthome Secara Pervasif Dengan Nodemcu Dan Smartphone Reva Ade Wardana; Agung Setia Budi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 2 (2021): Februari 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Smarthome or what we usually call smart home is a house or building equipped with high technology that allows various systems and devices at home to communicate with each other. In Indonesia alone, smarthome technology is still in the introductory and familiarization stage to the community, the challenge of the smarthome concept is entering the realm of the smallest and most intimate community, namely the family, There are so many ways to implement a smarthome in daily life, such as the use of sensors to detect changes in the physical or chemical environment, turning on or turning off devices using smartphones, or simply monitoring the condition of the house remotely. In addition, the concept of IoT (Internet of Things) is one part that cannot be separated in the development of this technology, this concept can greatly help humans to streamline their time and help carry out activities with this problem. this system parameters are used to monitor. There are four sensors to monitor the state of the house, this system works automatically without user intervention. Then the Pervasive Computing method will communicate between Nodes. In this study the estimated time used for communication between nodes is approximately 4578- 5097ms.
Analisis Perbandingan Pengalaman Pengguna Aplikasi Whatsapp dan Telegram menggunakan Kuesioner Mecue Alim Muhammad; Buce Trias Hanggara; Hanifah Muslimah Az-Zahra
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

User experience is how a person feels when using a service, product, or system. On February 8, 2021, WhatsApp as one of the most widely used applications today offers new policies such as data sharing, data forwarding to Facebook, data limitations in 2016 and encryption systems. The Whatsapp application lost a lot of users and switched to other instant messengers such as Telegram which has almost the same function as WhatsApp. Based on the issues that occurred, the researcher wanted to analyze the differences in user experience of Telegram and WhatsApp application users by using the Mecue questionnaire. the questionnaire was distributed to 54 respondents who had met the predetermined criteria. In the Mecue questionnaire there are 5 modules and 10 indicators, namely Usefulness, usability, visual aesthetics, status, commitment, positive emotions, negative emotions, product loyalty, intention to use and overall evaluation. This study resulted in a comparison of the average value of each indicator of the two applications where the Whatsapp application had a higher value in all indicators except for the visual aesthetics indicator.
Analisis Performansi Routing Protokol Ad-Hoc on Demand Distance Vector (AODV) dan Greedy Perimeter Coordinator Routing (GPCR) Terhadap Data Collision Pada Vehicular Ad-Hoc Network (VANET) Tyo Enos Revan Gultom; Heru Nurwarsito
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 13 (2020): Publikasi Khusus Tahun 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

VANET is a network that utilizes vehicles as nodes to exchange information and provides security and comfort for vehicle users. Its main characteristics are High Mobilility and Dynamic Network Topology. This characteristic allows data collision to occur, which is a condition where two or more nodes send data to the same destination at the same time. This situation causes the data transferred does not reach its destination so that the VANET function can be disrupted. Previous research stated that AODV is a better topology-based protocol compared to DSR and DSDV while GPCR is a position-based protocol with better performance than GPSR. This study presents an analysis of the effect of the two routing protocols on data collision and their performance analysis. Testing is based on changes in the number and speed of nodes with performance parameters throughput, packet delivery ratio (PDR), end-to-end delay, and collision rate. The results showed that the relationship between the two routing protocols to the collision rate was more dominantly affecting the results of the packet delivery ratio parameters. In performance analysis, AODV better at throughput and PDR with 48,05 kbps and 49,82 % while GPCR with 0,66 kbps and 7,3 % when there is a change in the number of nodes. When the node speed changes, throughput and PDR of AODV are 51,32 kbps and 33,34 % while GPCR are 0,585 kbps and 9,85 %. In end to end delay, GPCR is much better than AODV. On changes in the number and speed of nodes, each values ​​of AODV are 792.717 ms and 233.245 ms, and the values of GPCR are 14.528 ms and 5.252 ms.
Pengaruh Aspek Afektif terhadap Prestasi Belajar Pemrograman Web dan Perangkat Bergerak Studi Kasus Kelas X RPL SMK PGRI 3 Malang Annisa Mutiara Fari; Admaja Dwi Herlambang; Satrio Hadi Wijaya
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Curriculum-13 contains an assessment of affective attitudes that focuses on the feelings, interests, and talents of each student. Some examples of attitudes that students have are self-confidence, discipline, and responsibility. This study discusses the effect or impact of affective attitudes (confidence, discipline, and responsibility) on success in the learning process in Web and Mobile Programming subjects. Measurement of affective attitudes was measured using a questionnaire containing statements related to behavior in class. Measurement of learning achievement is taken from daily test scores for one semester. The population used is class X RPL SMK PGRI Malang with a total of 55 respondents. This study is classified as a quantitative study because the processed information is in the form of numbers. Using the comparative causal method in order to convey causal relationships that focus on cause and effect. The type of statistics used in this study is parametric statistics. Testing the data through the process of testing the validity and reliability. Meanwhile, data classification uses descriptive analysis. The results of the descriptive analysis on the affective aspects and student achievement showed that they were in the medium category. Proof of hypothesis based on multiple regression analysis by performing t test and f test. Statistical results show that self-confidence has an effect on learning achievement of Web and Mobile Programming by 8.80% in a negative direction. While the attitude of discipline has an effect of 29.00% in a positive direction and an attitude of responsibility has an effect of 11.20% in a positive direction.
Pengembangan Non-Player Character untuk 3D Kart Racing Game menggunakan Decision Tree Nashrul Azhar Mas'udi; Eriq Muhammad Adams Jonemaro; Muhammad Aminul Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 13 (2020): Publikasi Khusus Tahun 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Untuk dipublikasikan di Fountain of Informatics Journal (FIJ)
Pengaruh Nilai Radius terhadap Pemilihan Zona Optimal Protokol ZRP (Zone Routing Protocol) pada Lingkungan MANET (Mobile Adhoc Network) Daniel H. Simatupang; Primantara Hari Trisnawan; Rakhmadhany Primananda
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 6 (2020): Juni 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

A manet network is made up of moving nodes (mobile), each node that can establish communication with another without requiring a constant channel or template for that matter. The characteristic of manet is self-indulgence in which there is no need for a definition of infrastructure first. The kinds of protocols available in manet vary so much as proactive, reactive and hybrid protocols. The formation of zones depends on the manually designated radius values, the radius values has a significant share in the routing process. The observation of radius values affects the performance of ZRP's routing protocol using an NS-2 simulator. With a variation in number of nodes 20, 40, 60 and 80, variations in value radius 2, 3, 4 and 5 at area 1000m x 1000m using Random Way Point movements. Based on testing of ZRP's routing protocol with the packet delivery ratio (PDR), normalized routing load (NRL), end-to-end delay, throughput parameters with value radius 2 show better results in all test scenario for test parameters. For the parameters of the convergence time test, the value of radius 4 shows better on the entire test scenario.
Analisis Sentimen Masyarakat Indonesia terhadap Covid-19 pada Media Sosial Twitter menggunakan Metode Naive Bayes Tuahta Ramadhani; Yuita Arum Sari; Edy Santoso
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 12 (2021): Desember 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Twitter is often used by users to write or discuss issues and various topics that are currently happening. Twitter, which has many active users, is able to create a Twitter trending topic, where people are able to freely share information as well as the latest opinions on issues that are being discussed internationally. Not only as a liaison for socializing and interacting, Twitter can be used as a means of giving hope and showing about many things that are happening also in the community, such as in the case of the Covid-19 pandemic in Indonesia. With the emergence of the Covid-19 pandemic, it has caused various opinions from citizens, especially on Twitter social media users, especially the Indonesian people. Information about the views of residents is conveyed very quickly. there are those who defend and disagree regarding the information regarding the emergence of the Covid-19 pandemic. Everyone has their own thoughts and opinions, therefore this sentiment analysis can be applied to find out people's opinions on events that occur. In addition, in this study, sentiment analysis can be used to determine the level of accuracy based on data comments or opinions contained on Twitter social media. This study uses a classification strategy based on the Naive Bayes algorithm to classify text into three classes, namely positive, negative, and neutral. The use of this algorithm is also because it is a simple method. The difference between this study and previous research is the object of research which focuses on tweet comments related to Covid-19. From this study, it can be concluded that the results of the sentiment analysis system using the Naive Bayes method for Covid-19 data on Twitter and the level of accuracy with the Confusion Matrix are 87%.
Rancang Bangun Alat Pengenalan Papan Nama Ruangan pada Berbagai Kondisi Pencahayaan menggunakan Algoritme YOLOv3 berbasis NVIDIA Jetson Nano Asep Ranta Munajat; Fitri Utaminingrum
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Humans have a sense of sight that is able to obtain visual information in capturing objects far and near, but it is different from blind people. Blind people find it difficult to carry out daily activities such as walking in unfamiliar places and finding a room that is done independently. Several studies have made object detection devices to help visually impaired people through sound using a camera, lighting conditions affect the accuracy of detecting an object. The solution is to create a tool for blind people to recognize room signage in various lighting conditions using the Nvidia Jetson Nano-based YOLOv3 algorithm. This system adapts to 3 lighting conditions, namely dark (0-50 lux), dim (51-100 lux) and bright (101-500 lux) using a distance of 1 to 2.5 meters. The result of recognizing this room's nameplate is in the form of voice output. The test results are based on the LDR sensor response to lighting conditions of 100%, room nameplate recognition voice output of 100%, computational time obtained on LED light response and CLAHE mode of 1.891 seconds and room nameplate recognition of 0.40008 seconds. The average value of the whole system in recognizing the nameplate of the room under lighting conditions is 95.67%.

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